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Prompt Engineering

Checked
inference-sh·vlatest·ai-ml

Crafts optimized prompts for AI models to elicit desired outputs – boosting accuracy and effectiveness in your applications.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add inference-sh/skills --skill prompt-engineering -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

inference-sh

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned inference-sh/skills at c2d5678f14.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
c2d5678f14
Manifest
guides/prompting/prompt-engineering/SKILL.md
Scanned
1 file, 292 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

Prompt Engineering

What it does

This skill equips AI agents with advanced techniques to craft, refine, and optimize natural language instructions for better model performance. It enables agents to dynamically adjust their communication style and logic flow based on specific task requirements.

When to use it

  • Complex Reasoning Tasks: When an agent needs to solve multi-step problems requiring chain-of-thought reasoning or structured logic.
  • Role-Specific Interactions: To configure the agent to adopt a specific persona, tone, or expertise level for customer support or creative writing.
  • Output Formatting: When precise control over the structure of responses (e.g., JSON, Markdown tables) is required for downstream processing.
  • Constraint Adherence: To strictly enforce rules regarding length, vocabulary, or prohibited topics during generation.

Key capabilities

  • Dynamic prompt construction based on context variables.
  • Optimization of instruction clarity to reduce hallucinations.
  • Adaptation of output formats and stylistic tones.
  • Implementation of few-shot learning examples within prompts.

Example prompts

  • "Refine the following user query into a structured system instruction that ensures the agent outputs only valid JSON."
  • "Generate a prompt template for a coding assistant that enforces strict security best practices in all generated snippets."
  • "Optimize this dialogue script to make the AI persona sound more empathetic while maintaining factual accuracy."

Tips & gotchas

Effective use of this skill requires clear input data; vague instructions often lead to suboptimal prompt generation. Always validate the agent's output against your specific constraints, as advanced prompting can sometimes introduce complexity that obscures simple errors.